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-rw-r--r--test/CMakeLists.txt11
-rw-r--r--test/array.cpp2
-rw-r--r--test/cholesky.cpp64
-rw-r--r--test/fastmath.cpp2
-rw-r--r--test/geo_hyperplane.cpp10
-rw-r--r--test/geo_quaternion.cpp6
-rw-r--r--test/geo_transformations.cpp2
-rw-r--r--test/linearstructure.cpp3
-rw-r--r--test/lu.cpp23
-rw-r--r--test/main.h18
-rw-r--r--test/mixingtypes.cpp8
-rw-r--r--test/packetmath.cpp2
-rw-r--r--test/product_large.cpp2
-rw-r--r--test/qr_colpivoting.cpp2
-rw-r--r--test/rand.cpp3
-rw-r--r--test/sparse_basic.cpp4
-rw-r--r--test/sparse_block.cpp2
-rw-r--r--test/sparse_product.cpp2
-rw-r--r--test/sparse_vector.cpp2
-rw-r--r--test/sparseqr.cpp2
-rw-r--r--test/svd_common.h4
-rw-r--r--test/svd_fill.h14
-rw-r--r--test/swap.cpp11
-rw-r--r--test/triangular.cpp4
-rw-r--r--test/vectorization_logic.cpp49
25 files changed, 189 insertions, 63 deletions
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 841c4572b..7bed6a45c 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -327,8 +327,14 @@ endif()
# CUDA unit tests
option(EIGEN_TEST_CUDA "Enable CUDA support in unit tests" OFF)
+option(EIGEN_TEST_CUDA_CLANG "Use clang instead of nvcc to compile the CUDA tests" OFF)
+
+if(EIGEN_TEST_CUDA_CLANG AND NOT CMAKE_CXX_COMPILER MATCHES "clang")
+ message(WARNING "EIGEN_TEST_CUDA_CLANG is set, but CMAKE_CXX_COMPILER does not appear to be clang.")
+endif()
+
if(EIGEN_TEST_CUDA)
-
+
find_package(CUDA 5.0)
if(CUDA_FOUND)
@@ -336,6 +342,9 @@ if(CUDA_FOUND)
if("${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
set(CUDA_NVCC_FLAGS "-ccbin /usr/bin/clang" CACHE STRING "nvcc flags" FORCE)
endif()
+ if(EIGEN_TEST_CUDA_CLANG)
+ set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 --cuda-gpu-arch=sm_30")
+ endif()
cuda_include_directories(${CMAKE_CURRENT_BINARY_DIR})
set(EIGEN_ADD_TEST_FILENAME_EXTENSION "cu")
diff --git a/test/array.cpp b/test/array.cpp
index 8b0a34722..beaa62221 100644
--- a/test/array.cpp
+++ b/test/array.cpp
@@ -331,11 +331,13 @@ template<typename ArrayType> void array_real(const ArrayType& m)
VERIFY_IS_APPROX(numext::zeta(Scalar(3), Scalar(-2.5)), RealScalar(0.054102025820864097));
VERIFY_IS_EQUAL(numext::zeta(Scalar(1), Scalar(1.2345)), // The second scalar does not matter
std::numeric_limits<RealScalar>::infinity());
+ VERIFY((numext::isnan)(numext::zeta(Scalar(0.9), Scalar(1.2345)))); // The second scalar does not matter
// Check the polygamma against scipy.special.polygamma examples
VERIFY_IS_APPROX(numext::polygamma(Scalar(1), Scalar(2)), RealScalar(0.644934066848));
VERIFY_IS_APPROX(numext::polygamma(Scalar(1), Scalar(3)), RealScalar(0.394934066848));
VERIFY_IS_APPROX(numext::polygamma(Scalar(1), Scalar(25.5)), RealScalar(0.0399946696496));
+ VERIFY((numext::isnan)(numext::polygamma(Scalar(1.5), Scalar(1.2345)))); // The second scalar does not matter
// Check the polygamma function over a larger range of values
VERIFY_IS_APPROX(numext::polygamma(Scalar(17), Scalar(4.7)), RealScalar(293.334565435));
diff --git a/test/cholesky.cpp b/test/cholesky.cpp
index d652af5bf..b7abc230b 100644
--- a/test/cholesky.cpp
+++ b/test/cholesky.cpp
@@ -17,6 +17,12 @@
#include <Eigen/Cholesky>
#include <Eigen/QR>
+template<typename MatrixType, int UpLo>
+typename MatrixType::RealScalar matrix_l1_norm(const MatrixType& m) {
+ MatrixType symm = m.template selfadjointView<UpLo>();
+ return symm.cwiseAbs().colwise().sum().maxCoeff();
+}
+
template<typename MatrixType,template <typename,int> class CholType> void test_chol_update(const MatrixType& symm)
{
typedef typename MatrixType::Scalar Scalar;
@@ -77,7 +83,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
{
SquareMatrixType symmUp = symm.template triangularView<Upper>();
SquareMatrixType symmLo = symm.template triangularView<Lower>();
-
+
LLT<SquareMatrixType,Lower> chollo(symmLo);
VERIFY_IS_APPROX(symm, chollo.reconstructedMatrix());
vecX = chollo.solve(vecB);
@@ -85,6 +91,14 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
matX = chollo.solve(matB);
VERIFY_IS_APPROX(symm * matX, matB);
+ const MatrixType symmLo_inverse = chollo.solve(MatrixType::Identity(rows,cols));
+ RealScalar rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Lower>(symmLo)) /
+ matrix_l1_norm<MatrixType, Lower>(symmLo_inverse);
+ RealScalar rcond_est = chollo.rcond();
+ // Verify that the estimated condition number is within a factor of 10 of the
+ // truth.
+ VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
// test the upper mode
LLT<SquareMatrixType,Upper> cholup(symmUp);
VERIFY_IS_APPROX(symm, cholup.reconstructedMatrix());
@@ -93,6 +107,15 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
matX = cholup.solve(matB);
VERIFY_IS_APPROX(symm * matX, matB);
+ // Verify that the estimated condition number is within a factor of 10 of the
+ // truth.
+ const MatrixType symmUp_inverse = cholup.solve(MatrixType::Identity(rows,cols));
+ rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Upper>(symmUp)) /
+ matrix_l1_norm<MatrixType, Upper>(symmUp_inverse);
+ rcond_est = cholup.rcond();
+ VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
+
MatrixType neg = -symmLo;
chollo.compute(neg);
VERIFY(chollo.info()==NumericalIssue);
@@ -101,7 +124,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
VERIFY_IS_APPROX(MatrixType(chollo.matrixU().transpose().conjugate()), MatrixType(chollo.matrixL()));
VERIFY_IS_APPROX(MatrixType(cholup.matrixL().transpose().conjugate()), MatrixType(cholup.matrixU()));
VERIFY_IS_APPROX(MatrixType(cholup.matrixU().transpose().conjugate()), MatrixType(cholup.matrixL()));
-
+
// test some special use cases of SelfCwiseBinaryOp:
MatrixType m1 = MatrixType::Random(rows,cols), m2(rows,cols);
m2 = m1;
@@ -137,6 +160,15 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
matX = ldltlo.solve(matB);
VERIFY_IS_APPROX(symm * matX, matB);
+ const MatrixType symmLo_inverse = ldltlo.solve(MatrixType::Identity(rows,cols));
+ RealScalar rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Lower>(symmLo)) /
+ matrix_l1_norm<MatrixType, Lower>(symmLo_inverse);
+ RealScalar rcond_est = ldltlo.rcond();
+ // Verify that the estimated condition number is within a factor of 10 of the
+ // truth.
+ VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
+
LDLT<SquareMatrixType,Upper> ldltup(symmUp);
VERIFY_IS_APPROX(symm, ldltup.reconstructedMatrix());
vecX = ldltup.solve(vecB);
@@ -144,6 +176,14 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
matX = ldltup.solve(matB);
VERIFY_IS_APPROX(symm * matX, matB);
+ // Verify that the estimated condition number is within a factor of 10 of the
+ // truth.
+ const MatrixType symmUp_inverse = ldltup.solve(MatrixType::Identity(rows,cols));
+ rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Upper>(symmUp)) /
+ matrix_l1_norm<MatrixType, Upper>(symmUp_inverse);
+ rcond_est = ldltup.rcond();
+ VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
VERIFY_IS_APPROX(MatrixType(ldltlo.matrixL().transpose().conjugate()), MatrixType(ldltlo.matrixU()));
VERIFY_IS_APPROX(MatrixType(ldltlo.matrixU().transpose().conjugate()), MatrixType(ldltlo.matrixL()));
VERIFY_IS_APPROX(MatrixType(ldltup.matrixL().transpose().conjugate()), MatrixType(ldltup.matrixU()));
@@ -167,7 +207,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
// restore
if(sign == -1)
symm = -symm;
-
+
// check matrices coming from linear constraints with Lagrange multipliers
if(rows>=3)
{
@@ -183,7 +223,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
vecX = ldltlo.solve(vecB);
VERIFY_IS_APPROX(A * vecX, vecB);
}
-
+
// check non-full rank matrices
if(rows>=3)
{
@@ -199,7 +239,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
vecX = ldltlo.solve(vecB);
VERIFY_IS_APPROX(A * vecX, vecB);
}
-
+
// check matrices with a wide spectrum
if(rows>=3)
{
@@ -225,7 +265,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
{
RealScalar large_tol = std::sqrt(test_precision<RealScalar>());
VERIFY((A * vecX).isApprox(vecB, large_tol));
-
+
++g_test_level;
VERIFY_IS_APPROX(A * vecX,vecB);
--g_test_level;
@@ -314,14 +354,14 @@ template<typename MatrixType> void cholesky_bug241(const MatrixType& m)
}
// LDLT is not guaranteed to work for indefinite matrices, but happens to work fine if matrix is diagonal.
-// This test checks that LDLT reports correctly that matrix is indefinite.
+// This test checks that LDLT reports correctly that matrix is indefinite.
// See http://forum.kde.org/viewtopic.php?f=74&t=106942 and bug 736
template<typename MatrixType> void cholesky_definiteness(const MatrixType& m)
{
eigen_assert(m.rows() == 2 && m.cols() == 2);
MatrixType mat;
LDLT<MatrixType> ldlt(2);
-
+
{
mat << 1, 0, 0, -1;
ldlt.compute(mat);
@@ -384,11 +424,11 @@ void test_cholesky()
CALL_SUBTEST_3( cholesky_definiteness(Matrix2d()) );
CALL_SUBTEST_4( cholesky(Matrix3f()) );
CALL_SUBTEST_5( cholesky(Matrix4d()) );
-
- s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
+
+ s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
CALL_SUBTEST_2( cholesky(MatrixXd(s,s)) );
TEST_SET_BUT_UNUSED_VARIABLE(s)
-
+
s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
CALL_SUBTEST_6( cholesky_cplx(MatrixXcd(s,s)) );
TEST_SET_BUT_UNUSED_VARIABLE(s)
@@ -402,6 +442,6 @@ void test_cholesky()
// Test problem size constructors
CALL_SUBTEST_9( LLT<MatrixXf>(10) );
CALL_SUBTEST_9( LDLT<MatrixXf>(10) );
-
+
TEST_SET_BUT_UNUSED_VARIABLE(nb_temporaries)
}
diff --git a/test/fastmath.cpp b/test/fastmath.cpp
index efdd5b313..438e6b2e5 100644
--- a/test/fastmath.cpp
+++ b/test/fastmath.cpp
@@ -49,7 +49,7 @@ void check_inf_nan(bool dryrun) {
VERIFY( !m.allFinite() );
VERIFY( m.hasNaN() );
}
- m(4) /= 0.0;
+ m(4) /= T(0.0);
if(dryrun)
{
std::cout << "std::isfinite(" << m(4) << ") = "; check((std::isfinite)(m(4)),false); std::cout << " ; numext::isfinite = "; check((numext::isfinite)(m(4)), false); std::cout << "\n";
diff --git a/test/geo_hyperplane.cpp b/test/geo_hyperplane.cpp
index c1cc691c9..e77702bc7 100644
--- a/test/geo_hyperplane.cpp
+++ b/test/geo_hyperplane.cpp
@@ -97,9 +97,9 @@ template<typename Scalar> void lines()
Vector u = Vector::Random();
Vector v = Vector::Random();
Scalar a = internal::random<Scalar>();
- while (abs(a-1) < 1e-4) a = internal::random<Scalar>();
- while (u.norm() < 1e-4) u = Vector::Random();
- while (v.norm() < 1e-4) v = Vector::Random();
+ while (abs(a-1) < Scalar(1e-4)) a = internal::random<Scalar>();
+ while (u.norm() < Scalar(1e-4)) u = Vector::Random();
+ while (v.norm() < Scalar(1e-4)) v = Vector::Random();
HLine line_u = HLine::Through(center + u, center + a*u);
HLine line_v = HLine::Through(center + v, center + a*v);
@@ -111,14 +111,14 @@ template<typename Scalar> void lines()
Vector result = line_u.intersection(line_v);
// the lines should intersect at the point we called "center"
- if(abs(a-1) > 1e-2 && abs(v.normalized().dot(u.normalized()))<0.9)
+ if(abs(a-1) > Scalar(1e-2) && abs(v.normalized().dot(u.normalized()))<Scalar(0.9))
VERIFY_IS_APPROX(result, center);
// check conversions between two types of lines
PLine pl(line_u); // gcc 3.3 will commit suicide if we don't name this variable
HLine line_u2(pl);
CoeffsType converted_coeffs = line_u2.coeffs();
- if(line_u2.normal().dot(line_u.normal())<0.)
+ if(line_u2.normal().dot(line_u.normal())<Scalar(0))
converted_coeffs = -line_u2.coeffs();
VERIFY(line_u.coeffs().isApprox(converted_coeffs));
}
diff --git a/test/geo_quaternion.cpp b/test/geo_quaternion.cpp
index 761bb52b4..25130c19a 100644
--- a/test/geo_quaternion.cpp
+++ b/test/geo_quaternion.cpp
@@ -30,7 +30,7 @@ template<typename QuatType> void check_slerp(const QuatType& q0, const QuatType&
Scalar largeEps = test_precision<Scalar>();
Scalar theta_tot = AA(q1*q0.inverse()).angle();
- if(theta_tot>EIGEN_PI)
+ if(theta_tot>Scalar(EIGEN_PI))
theta_tot = Scalar(2.*EIGEN_PI)-theta_tot;
for(Scalar t=0; t<=Scalar(1.001); t+=Scalar(0.1))
{
@@ -115,8 +115,8 @@ template<typename Scalar, int Options> void quaternion(void)
// Do not execute the test if the rotation angle is almost zero, or
// the rotation axis and v1 are almost parallel.
if (abs(aa.angle()) > 5*test_precision<Scalar>()
- && (aa.axis() - v1.normalized()).norm() < 1.99
- && (aa.axis() + v1.normalized()).norm() < 1.99)
+ && (aa.axis() - v1.normalized()).norm() < Scalar(1.99)
+ && (aa.axis() + v1.normalized()).norm() < Scalar(1.99))
{
VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
}
diff --git a/test/geo_transformations.cpp b/test/geo_transformations.cpp
index 51f90036d..48393a5c6 100644
--- a/test/geo_transformations.cpp
+++ b/test/geo_transformations.cpp
@@ -466,7 +466,7 @@ template<typename Scalar, int Mode, int Options> void transformations()
Scalar a2 = R0.slerp(Scalar(k+1)/Scalar(path_steps), R1).angle();
l += std::abs(a2-a1);
}
- VERIFY(l<=EIGEN_PI*(Scalar(1)+NumTraits<Scalar>::epsilon()*Scalar(path_steps/2)));
+ VERIFY(l<=Scalar(EIGEN_PI)*(Scalar(1)+NumTraits<Scalar>::epsilon()*Scalar(path_steps/2)));
// check basic features
{
diff --git a/test/linearstructure.cpp b/test/linearstructure.cpp
index 292f33969..e7f4b3dc5 100644
--- a/test/linearstructure.cpp
+++ b/test/linearstructure.cpp
@@ -21,6 +21,7 @@ template<typename MatrixType> void linearStructure(const MatrixType& m)
*/
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
+ typedef typename MatrixType::RealScalar RealScalar;
Index rows = m.rows();
Index cols = m.cols();
@@ -32,7 +33,7 @@ template<typename MatrixType> void linearStructure(const MatrixType& m)
m3(rows, cols);
Scalar s1 = internal::random<Scalar>();
- while (abs(s1)<1e-3) s1 = internal::random<Scalar>();
+ while (abs(s1)<RealScalar(1e-3)) s1 = internal::random<Scalar>();
Index r = internal::random<Index>(0, rows-1),
c = internal::random<Index>(0, cols-1);
diff --git a/test/lu.cpp b/test/lu.cpp
index f14435114..9787f4d86 100644
--- a/test/lu.cpp
+++ b/test/lu.cpp
@@ -11,6 +11,11 @@
#include <Eigen/LU>
using namespace std;
+template<typename MatrixType>
+typename MatrixType::RealScalar matrix_l1_norm(const MatrixType& m) {
+ return m.cwiseAbs().colwise().sum().maxCoeff();
+}
+
template<typename MatrixType> void lu_non_invertible()
{
typedef typename MatrixType::Index Index;
@@ -143,7 +148,14 @@ template<typename MatrixType> void lu_invertible()
m3 = MatrixType::Random(size,size);
m2 = lu.solve(m3);
VERIFY_IS_APPROX(m3, m1*m2);
- VERIFY_IS_APPROX(m2, lu.inverse()*m3);
+ MatrixType m1_inverse = lu.inverse();
+ VERIFY_IS_APPROX(m2, m1_inverse*m3);
+
+ RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse);
+ const RealScalar rcond_est = lu.rcond();
+ // Verify that the estimated condition number is within a factor of 10 of the
+ // truth.
+ VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
// test solve with transposed
lu.template _solve_impl_transposed<false>(m3, m2);
@@ -170,6 +182,7 @@ template<typename MatrixType> void lu_partial_piv()
PartialPivLU.h
*/
typedef typename MatrixType::Index Index;
+ typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
Index size = internal::random<Index>(1,4);
MatrixType m1(size, size), m2(size, size), m3(size, size);
@@ -181,7 +194,13 @@ template<typename MatrixType> void lu_partial_piv()
m3 = MatrixType::Random(size,size);
m2 = plu.solve(m3);
VERIFY_IS_APPROX(m3, m1*m2);
- VERIFY_IS_APPROX(m2, plu.inverse()*m3);
+ MatrixType m1_inverse = plu.inverse();
+ VERIFY_IS_APPROX(m2, m1_inverse*m3);
+
+ RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse);
+ const RealScalar rcond_est = plu.rcond();
+ // Verify that the estimate is within a factor of 10 of the truth.
+ VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
// test solve with transposed
plu.template _solve_impl_transposed<false>(m3, m2);
diff --git a/test/main.h b/test/main.h
index bba5e7570..1bfb9e1b0 100644
--- a/test/main.h
+++ b/test/main.h
@@ -275,6 +275,10 @@ inline void verify_impl(bool condition, const char *testname, const char *file,
#define VERIFY(a) ::verify_impl(a, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a))
+#define VERIFY_GE(a, b) ::verify_impl(a >= b, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a >= b))
+#define VERIFY_LE(a, b) ::verify_impl(a <= b, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a <= b))
+
+
#define VERIFY_IS_EQUAL(a, b) VERIFY(test_is_equal(a, b))
#define VERIFY_IS_NOT_EQUAL(a, b) VERIFY(!test_is_equal(a, b))
#define VERIFY_IS_APPROX(a, b) VERIFY(verifyIsApprox(a, b))
@@ -298,7 +302,7 @@ namespace Eigen {
template<typename T> inline typename NumTraits<T>::Real test_precision() { return NumTraits<T>::dummy_precision(); }
template<> inline float test_precision<float>() { return 1e-3f; }
template<> inline double test_precision<double>() { return 1e-6; }
-template<> inline long double test_precision<long double>() { return 1e-6; }
+template<> inline long double test_precision<long double>() { return 1e-6l; }
template<> inline float test_precision<std::complex<float> >() { return test_precision<float>(); }
template<> inline double test_precision<std::complex<double> >() { return test_precision<double>(); }
template<> inline long double test_precision<std::complex<long double> >() { return test_precision<long double>(); }
@@ -316,9 +320,9 @@ inline bool test_isMuchSmallerThan(const float& a, const float& b)
{ return internal::isMuchSmallerThan(a, b, test_precision<float>()); }
inline bool test_isApproxOrLessThan(const float& a, const float& b)
{ return internal::isApproxOrLessThan(a, b, test_precision<float>()); }
+
inline bool test_isApprox(const double& a, const double& b)
{ return internal::isApprox(a, b, test_precision<double>()); }
-
inline bool test_isMuchSmallerThan(const double& a, const double& b)
{ return internal::isMuchSmallerThan(a, b, test_precision<double>()); }
inline bool test_isApproxOrLessThan(const double& a, const double& b)
@@ -359,6 +363,12 @@ inline bool test_isApproxOrLessThan(const long double& a, const long double& b)
{ return internal::isApproxOrLessThan(a, b, test_precision<long double>()); }
#endif // EIGEN_TEST_NO_LONGDOUBLE
+inline bool test_isApprox(const half& a, const half& b)
+{ return internal::isApprox(a, b, test_precision<half>()); }
+inline bool test_isMuchSmallerThan(const half& a, const half& b)
+{ return internal::isMuchSmallerThan(a, b, test_precision<half>()); }
+inline bool test_isApproxOrLessThan(const half& a, const half& b)
+{ return internal::isApproxOrLessThan(a, b, test_precision<half>()); }
// test_relative_error returns the relative difference between a and b as a real scalar as used in isApprox.
template<typename T1,typename T2>
@@ -426,9 +436,7 @@ template<typename T1,typename T2>
typename NumTraits<T1>::Real test_relative_error(const T1 &a, const T2 &b, typename internal::enable_if<internal::is_arithmetic<typename NumTraits<T1>::Real>::value, T1>::type* = 0)
{
typedef typename NumTraits<T1>::Real RealScalar;
- using std::min;
- using std::sqrt;
- return sqrt(RealScalar(numext::abs2(a-b))/RealScalar((min)(numext::abs2(a),numext::abs2(b))));
+ return numext::sqrt(RealScalar(numext::abs2(a-b))/RealScalar((numext::mini)(numext::abs2(a),numext::abs2(b))));
}
template<typename T>
diff --git a/test/mixingtypes.cpp b/test/mixingtypes.cpp
index a3b469af8..0b381ec6c 100644
--- a/test/mixingtypes.cpp
+++ b/test/mixingtypes.cpp
@@ -148,10 +148,14 @@ template<int SizeAtCompileType> void mixingtypes(int size = SizeAtCompileType)
VERIFY_IS_APPROX(sd*vd.adjoint()*mcd, sd*vd.adjoint().template cast<CD>().eval()*mcd);
VERIFY_IS_APPROX(scd*vd.adjoint()*mcd, scd*vd.adjoint().template cast<CD>().eval()*mcd);
- VERIFY_IS_APPROX(sd*vcd.adjoint()*md.template triangularView<Upper>(), sd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Upper>());
+ VERIFY_IS_APPROX( sd*vcd.adjoint()*md.template triangularView<Upper>(), sd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Upper>());
VERIFY_IS_APPROX(scd*vcd.adjoint()*md.template triangularView<Lower>(), scd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Lower>());
- VERIFY_IS_APPROX(sd*vd.adjoint()*mcd.template triangularView<Lower>(), sd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Lower>());
+ VERIFY_IS_APPROX( sd*vcd.adjoint()*md.transpose().template triangularView<Upper>(), sd*vcd.adjoint()*md.transpose().template cast<CD>().eval().template triangularView<Upper>());
+ VERIFY_IS_APPROX(scd*vcd.adjoint()*md.transpose().template triangularView<Lower>(), scd*vcd.adjoint()*md.transpose().template cast<CD>().eval().template triangularView<Lower>());
+ VERIFY_IS_APPROX( sd*vd.adjoint()*mcd.template triangularView<Lower>(), sd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Lower>());
VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.template triangularView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Upper>());
+ VERIFY_IS_APPROX( sd*vd.adjoint()*mcd.transpose().template triangularView<Lower>(), sd*vd.adjoint().template cast<CD>().eval()*mcd.transpose().template triangularView<Lower>());
+ VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.transpose().template triangularView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.transpose().template triangularView<Upper>());
// Not supported yet: trmm
// VERIFY_IS_APPROX(sd*mcd*md.template triangularView<Lower>(), sd*mcd*md.template cast<CD>().eval().template triangularView<Lower>());
diff --git a/test/packetmath.cpp b/test/packetmath.cpp
index 37da6c86f..7f5a6512d 100644
--- a/test/packetmath.cpp
+++ b/test/packetmath.cpp
@@ -387,7 +387,7 @@ template<typename Scalar> void packetmath_real()
data2[i] = internal::random<Scalar>(0,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
}
- if(internal::random<float>(0,1)<0.1)
+ if(internal::random<float>(0,1)<0.1f)
data1[internal::random<int>(0, PacketSize)] = 0;
CHECK_CWISE1_IF(PacketTraits::HasSqrt, std::sqrt, internal::psqrt);
CHECK_CWISE1_IF(PacketTraits::HasLog, std::log, internal::plog);
diff --git a/test/product_large.cpp b/test/product_large.cpp
index 98f84c53b..845cd40ca 100644
--- a/test/product_large.cpp
+++ b/test/product_large.cpp
@@ -71,7 +71,7 @@ void test_product_large()
std::ptrdiff_t m1 = internal::random<int>(10,100)*16;
std::ptrdiff_t n1 = internal::random<int>(10,100)*16;
// only makes sure it compiles fine
- internal::computeProductBlockingSizes<float,float>(k1,m1,n1,1);
+ internal::computeProductBlockingSizes<float,float,std::ptrdiff_t>(k1,m1,n1,1);
}
{
diff --git a/test/qr_colpivoting.cpp b/test/qr_colpivoting.cpp
index 46c54b74f..ef3a6173b 100644
--- a/test/qr_colpivoting.cpp
+++ b/test/qr_colpivoting.cpp
@@ -206,7 +206,7 @@ template<typename MatrixType> void qr_kahan_matrix()
RealScalar c = std::sqrt(1 - s*s);
for (Index i = 0; i < rows; ++i) {
m1(i, i) = pow(s, i);
- m1.row(i).tail(rows - i - 1) = -pow(s, i) * c * MatrixType::Ones(1, rows - i - 1);
+ m1.row(i).tail(rows - i - 1) = -RealScalar(pow(s, i)) * c * MatrixType::Ones(1, rows - i - 1);
}
m1 = (m1 + m1.transpose()).eval();
ColPivHouseholderQR<MatrixType> qr(m1);
diff --git a/test/rand.cpp b/test/rand.cpp
index 6790acf15..eeec34191 100644
--- a/test/rand.cpp
+++ b/test/rand.cpp
@@ -29,6 +29,9 @@ template<typename Scalar> void check_all_in_range(Scalar x, Scalar y)
{
mask( check_in_range(x,y)-x )++;
}
+ for(Index i=0; i<mask.size(); ++i)
+ if(mask(i)==0)
+ std::cout << "WARNING: value " << x+i << " not reached." << std::endl;
VERIFY( (mask>0).all() );
}
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp
index cb8ebaedf..aa3882583 100644
--- a/test/sparse_basic.cpp
+++ b/test/sparse_basic.cpp
@@ -232,11 +232,11 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
for (Index i=0; i<m2.rows(); ++i)
{
float x = internal::random<float>(0,1);
- if (x<0.1)
+ if (x<0.1f)
{
// do nothing
}
- else if (x<0.5)
+ else if (x<0.5f)
{
countFalseNonZero++;
m2.insert(i,j) = Scalar(0);
diff --git a/test/sparse_block.cpp b/test/sparse_block.cpp
index 8a6e0687c..582bf34c3 100644
--- a/test/sparse_block.cpp
+++ b/test/sparse_block.cpp
@@ -150,7 +150,7 @@ template<typename SparseMatrixType> void sparse_block(const SparseMatrixType& re
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m2(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
- if(internal::random<float>(0,1)>0.5) m2.makeCompressed();
+ if(internal::random<float>(0,1)>0.5f) m2.makeCompressed();
Index j0 = internal::random<Index>(0,outer-2);
Index j1 = internal::random<Index>(0,outer-2);
Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp
index 7ec5270e8..501aeeaa6 100644
--- a/test/sparse_product.cpp
+++ b/test/sparse_product.cpp
@@ -245,7 +245,7 @@ template<typename SparseMatrixType> void sparse_product()
for (int k=0; k<mS.outerSize(); ++k)
for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
if (it.index() == k)
- it.valueRef() *= 0.5;
+ it.valueRef() *= Scalar(0.5);
VERIFY_IS_APPROX(refS.adjoint(), refS);
VERIFY_IS_APPROX(mS.adjoint(), mS);
diff --git a/test/sparse_vector.cpp b/test/sparse_vector.cpp
index d95f301d5..b3e1dda25 100644
--- a/test/sparse_vector.cpp
+++ b/test/sparse_vector.cpp
@@ -12,7 +12,7 @@
template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int cols)
{
double densityMat = (std::max)(8./(rows*cols), 0.01);
- double densityVec = (std::max)(8./float(rows), 0.1);
+ double densityVec = (std::max)(8./(rows), 0.1);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef SparseVector<Scalar,0,StorageIndex> SparseVectorType;
diff --git a/test/sparseqr.cpp b/test/sparseqr.cpp
index 50d1fcdf2..e8605fd21 100644
--- a/test/sparseqr.cpp
+++ b/test/sparseqr.cpp
@@ -54,7 +54,7 @@ template<typename Scalar> void test_sparseqr_scalar()
b = dA * DenseVector::Random(A.cols());
solver.compute(A);
- if(internal::random<float>(0,1)>0.5)
+ if(internal::random<float>(0,1)>0.5f)
solver.factorize(A); // this checks that calling analyzePattern is not needed if the pattern do not change.
if (solver.info() != Success)
{
diff --git a/test/svd_common.h b/test/svd_common.h
index d8611b541..3588eefaa 100644
--- a/test/svd_common.h
+++ b/test/svd_common.h
@@ -141,14 +141,14 @@ void svd_least_square(const MatrixType& m, unsigned int computationOptions)
using std::abs;
SolutionType y(x);
- y.row(k) = (1.+2*NumTraits<RealScalar>::epsilon())*x.row(k);
+ y.row(k) = (RealScalar(1)+2*NumTraits<RealScalar>::epsilon())*x.row(k);
RealScalar residual_y = (m*y-rhs).norm();
VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
if(internal::is_same<RealScalar,float>::value) ++g_test_level;
VERIFY( test_isApprox(residual_y,residual) || residual < residual_y );
if(internal::is_same<RealScalar,float>::value) --g_test_level;
- y.row(k) = (1.-2*NumTraits<RealScalar>::epsilon())*x.row(k);
+ y.row(k) = (RealScalar(1)-2*NumTraits<RealScalar>::epsilon())*x.row(k);
residual_y = (m*y-rhs).norm();
VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
if(internal::is_same<RealScalar,float>::value) ++g_test_level;
diff --git a/test/svd_fill.h b/test/svd_fill.h
index 7e44b3d05..500954d47 100644
--- a/test/svd_fill.h
+++ b/test/svd_fill.h
@@ -54,7 +54,7 @@ void svd_fill_random(MatrixType &m, int Option = 0)
}
Matrix<Scalar,Dynamic,1> samples(7);
- samples << 0, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -1./NumTraits<RealScalar>::highest(), 1./NumTraits<RealScalar>::highest();
+ samples << 0, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -RealScalar(1)/NumTraits<RealScalar>::highest(), RealScalar(1)/NumTraits<RealScalar>::highest();
if(Option==Symmetric)
{
@@ -80,6 +80,8 @@ void svd_fill_random(MatrixType &m, int Option = 0)
Index i = internal::random<Index>(0,m.rows()-1);
Index j = internal::random<Index>(0,m.cols()-1);
m(j,i) = m(i,j) = samples(internal::random<Index>(0,samples.size()-1));
+ if(NumTraits<Scalar>::IsComplex)
+ *(&numext::real_ref(m(j,i))+1) = *(&numext::real_ref(m(i,j))+1) = samples.real()(internal::random<Index>(0,samples.size()-1));
}
}
}
@@ -91,8 +93,14 @@ void svd_fill_random(MatrixType &m, int Option = 0)
if(!(dup && unit_uv))
{
Index n = internal::random<Index>(0,m.size()-1);
- for(Index i=0; i<n; ++i)
- m(internal::random<Index>(0,m.rows()-1), internal::random<Index>(0,m.cols()-1)) = samples(internal::random<Index>(0,samples.size()-1));
+ for(Index k=0; k<n; ++k)
+ {
+ Index i = internal::random<Index>(0,m.rows()-1);
+ Index j = internal::random<Index>(0,m.cols()-1);
+ m(i,j) = samples(internal::random<Index>(0,samples.size()-1));
+ if(NumTraits<Scalar>::IsComplex)
+ *(&numext::real_ref(m(i,j))+1) = samples.real()(internal::random<Index>(0,samples.size()-1));
+ }
}
}
}
diff --git a/test/swap.cpp b/test/swap.cpp
index 5d6f0e6af..f76e3624d 100644
--- a/test/swap.cpp
+++ b/test/swap.cpp
@@ -74,10 +74,13 @@ template<typename MatrixType> void swap(const MatrixType& m)
m1 = m1_copy;
m3 = m3_copy;
- // test assertion on mismatching size -- matrix case
- VERIFY_RAISES_ASSERT(m1.swap(m1.row(0)));
- // test assertion on mismatching size -- xpr case
- VERIFY_RAISES_ASSERT(m1.row(0).swap(m1));
+ if(m1.rows()>1)
+ {
+ // test assertion on mismatching size -- matrix case
+ VERIFY_RAISES_ASSERT(m1.swap(m1.row(0)));
+ // test assertion on mismatching size -- xpr case
+ VERIFY_RAISES_ASSERT(m1.row(0).swap(m1));
+ }
}
void test_swap()
diff --git a/test/triangular.cpp b/test/triangular.cpp
index 936c2aef3..3e120f406 100644
--- a/test/triangular.cpp
+++ b/test/triangular.cpp
@@ -65,7 +65,7 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
m1 = MatrixType::Random(rows, cols);
for (int i=0; i<rows; ++i)
- while (numext::abs2(m1(i,i))<1e-1) m1(i,i) = internal::random<Scalar>();
+ while (numext::abs2(m1(i,i))<RealScalar(1e-1)) m1(i,i) = internal::random<Scalar>();
Transpose<MatrixType> trm4(m4);
// test back and forward subsitution with a vector as the rhs
@@ -78,7 +78,7 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
m3 = m1.template triangularView<Lower>();
VERIFY(v2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(v2)), largerEps));
- // test back and forward subsitution with a matrix as the rhs
+ // test back and forward substitution with a matrix as the rhs
m3 = m1.template triangularView<Upper>();
VERIFY(m2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(m2)), largerEps));
m3 = m1.template triangularView<Lower>();
diff --git a/test/vectorization_logic.cpp b/test/vectorization_logic.cpp
index 35fbb9781..ee446c3c1 100644
--- a/test/vectorization_logic.cpp
+++ b/test/vectorization_logic.cpp
@@ -22,7 +22,11 @@ template<typename Dst, typename Src>
bool test_assign(const Dst&, const Src&, int traversal, int unrolling)
{
typedef internal::copy_using_evaluator_traits<internal::evaluator<Dst>,internal::evaluator<Src>, internal::assign_op<typename Dst::Scalar> > traits;
- bool res = traits::Traversal==traversal && traits::Unrolling==unrolling;
+ bool res = traits::Traversal==traversal;
+ if(unrolling==InnerUnrolling+CompleteUnrolling)
+ res = res && (int(traits::Unrolling)==InnerUnrolling || int(traits::Unrolling)==CompleteUnrolling);
+ else
+ res = res && int(traits::Unrolling)==unrolling;
if(!res)
{
std::cerr << "Src: " << demangle_flags(Src::Flags) << std::endl;
@@ -147,10 +151,10 @@ struct vectorization_logic
VERIFY(test_assign(Matrix44c().col(1),Matrix44c().col(2)+Matrix44c().col(3),
InnerVectorizedTraversal,CompleteUnrolling));
-
+
VERIFY(test_assign(Matrix44r().row(2),Matrix44r().row(1)+Matrix44r().row(1),
InnerVectorizedTraversal,CompleteUnrolling));
-
+
if(PacketSize>1)
{
typedef Matrix<Scalar,3,3,ColMajor> Matrix33c;
@@ -158,17 +162,29 @@ struct vectorization_logic
LinearTraversal,CompleteUnrolling));
VERIFY(test_assign(Matrix33c().col(0),Matrix33c().col(1)+Matrix33c().col(1),
LinearTraversal,CompleteUnrolling));
-
- VERIFY(test_assign(Matrix3(),Matrix3().cwiseQuotient(Matrix3()),
- PacketTraits::HasDiv ? LinearVectorizedTraversal : LinearTraversal,CompleteUnrolling));
-
+
+ VERIFY(test_assign(Matrix3(),Matrix3().cwiseProduct(Matrix3()),
+ LinearVectorizedTraversal,CompleteUnrolling));
+
VERIFY(test_assign(Matrix<Scalar,17,17>(),Matrix<Scalar,17,17>()+Matrix<Scalar,17,17>(),
HalfPacketSize==1 ? InnerVectorizedTraversal : LinearTraversal,NoUnrolling));
-
+
VERIFY(test_assign(Matrix11(),Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(2,3)+Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(8,4),
DefaultTraversal,PacketSize>4?InnerUnrolling:CompleteUnrolling));
+
+ VERIFY(test_assign(Vector1(),Matrix11()*Vector1(),
+ InnerVectorizedTraversal,CompleteUnrolling));
+
+ VERIFY(test_assign(Matrix11(),Matrix11().lazyProduct(Matrix11()),
+ InnerVectorizedTraversal,InnerUnrolling+CompleteUnrolling));
}
-
+
+ VERIFY(test_redux(Vector1(),
+ LinearVectorizedTraversal,CompleteUnrolling));
+
+ VERIFY(test_redux(Matrix<Scalar,PacketSize,3>(),
+ LinearVectorizedTraversal,CompleteUnrolling));
+
VERIFY(test_redux(Matrix3(),
LinearVectorizedTraversal,CompleteUnrolling));
@@ -226,6 +242,7 @@ struct vectorization_logic_half
typedef Matrix<Scalar,PacketSize,1> Vector1;
typedef Matrix<Scalar,PacketSize,PacketSize> Matrix11;
typedef Matrix<Scalar,5*PacketSize,7,ColMajor> Matrix57;
+ typedef Matrix<Scalar,3*PacketSize,5,ColMajor> Matrix35;
typedef Matrix<Scalar,5*PacketSize,7,DontAlign|ColMajor> Matrix57u;
// typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16> Matrix44;
// typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16,DontAlign|EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION> Matrix44u;
@@ -291,12 +308,24 @@ struct vectorization_logic_half
VERIFY(test_assign(Matrix11(),Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(2,3)+Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(8,4),
DefaultTraversal,PacketSize>4?InnerUnrolling:CompleteUnrolling));
+
+ VERIFY(test_assign(Vector1(),Matrix11()*Vector1(),
+ InnerVectorizedTraversal,CompleteUnrolling));
+
+ VERIFY(test_assign(Matrix11(),Matrix11().lazyProduct(Matrix11()),
+ InnerVectorizedTraversal,InnerUnrolling+CompleteUnrolling));
}
+ VERIFY(test_redux(Vector1(),
+ LinearVectorizedTraversal,CompleteUnrolling));
+
+ VERIFY(test_redux(Matrix<Scalar,PacketSize,3>(),
+ LinearVectorizedTraversal,CompleteUnrolling));
+
VERIFY(test_redux(Matrix3(),
LinearVectorizedTraversal,CompleteUnrolling));
- VERIFY(test_redux(Matrix57(),
+ VERIFY(test_redux(Matrix35(),
LinearVectorizedTraversal,CompleteUnrolling));
VERIFY(test_redux(Matrix57().template block<PacketSize,3>(1,0),
generated by cgit v1.2.3 (git 2.39.1) at 2024-10-02 21:50:13 +0000